Adaptive Traffic Lights Could Achieve 'The Green Wave'

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Adaptive Traffic Lights Could Achieve 'The Green Wave'

Traffic lights that act locally can improve traffic globally, new research suggests. By minimizing congestion, the approach could save money, reduce emissions and perhaps even quash the road rage of frustrated drivers.

The new approach makes traffic lights go with the flow, rather than enslaving drivers to the tyranny of timed signals. By measuring vehicle inflow and outflow through each intersection as it occurs and coordinating lights with only their nearest neighbors, a system-wide smoothness emerges, scientists report in a September Santa Fe Institute working paper.

“It’s very interesting — the approach is adaptive and the system can react,” says mechanical engineer Gábor Orosz of the University of Michigan in Ann Arbor. “That’s how it should be — that’s how we can get the most out of our current system.”

An ultimate goal in traffic regulation is “the green wave,” the bam, bam, bam of greens that allows platoons of vehicles to move smoothly through intersection after intersection. When that happens, no drivers have to wait very long and sections of road don’t become so filled with cars that there’s no room for entering vehicles when the light does go green.

To achieve this rare bliss, traffic lights usually are controlled from the top down, operating on an “optimal” cycle that maximizes the flow of traffic expected for particular times of day, such as rush hour. But even for a typical time on a typical day, there’s so much variability in the number of cars at each light and the direction each car takes leaving an intersection that roads can fill up. Combine this condition with overzealous drivers, and intersections easily become gridlocked. Equally frustrating is the opposite extreme, where a driver sits at a red light for minutes even though there’s no car in sight to take advantage of the intersecting green.

“It is actually not optimal control, because that average situation never occurs,” says complex-systems scientist Dirk Helbing of the Swiss Federal Institute of Technology Zurich, a co-author of the new study. “Because of the large variability in the number of cars behind each red light, it means that although we have an optimal scheme, it’s optimal for a situation that does not occur.”

Helbing and his colleague Stefan Lämmer from the Dresden University of Technology in Germany decided to scrap the top-down approach and start at the bottom. They noted that when crowds of people are trying to move through a narrow space, such as through a door connecting two hallways, there’s a natural oscillation: A mass of people from one side will move through the door while the other people wait, then suddenly the flow switches direction.

“It looks like maybe there’s a traffic light, but there’s not. It’s actually the buildup of pressure on the side where people have to wait that eventually turns the flow direction,” says Helbing. “We thought we could maybe apply the same principle to intersections, that is, the traffic flow controls the traffic light rather than the other way around.”

Their arrangement puts two sensors at each intersection: One measures incoming flow and one measures outgoing flow. Lights are coordinated with every neighboring light, such that one light alerts the next, “Hey, heavy load coming through.”

That short-term anticipation gives lights at the next intersection enough time to prepare for the incoming platoon of vehicles, says Helbing. The whole point is to avoid stopping an incoming platoon. “It works surprisingly well,” he says. Gaps between platoons are opportunities to serve flows in other directions, and this local coordination naturally spreads throughout the system.

“It’s a paradoxical effect that occurs in complex systems,” says Helbing. “Surprisingly, delay processes can improve the system altogether. It is a slower-is-faster effect. You can increase the throughput — speed up the whole system — if you delay single processes within the system at the right time, for the right amount of time.”

The researchers ran a simulation of their approach in the city center of Dresden. The area has 13 traffic light–controlled intersections, 68 pedestrian crossings, a train station that serves more than 13,000 passengers on an average day and seven bus and tram lines that cross the network every 10 minutes in opposite directions. The flexible self-control approach reduced time stuck waiting in traffic by 56 percent for trams and buses, 9 percent for cars and trucks, and 36 percent for pedestrians crossing intersections. Dresden is now close to implementing the new system, says Helbing, and Zurich is also considering the approach.

Traffic jams aren’t just infuriating, they cost time and money, says Orosz. Estimates suggest that in one year, the U.S. driving population spends a cumulative 500,000 years in traffic at a cost of about $100 billion. And the roads are just going to get more congested. The optimal way of dealing with such congestion is to take an approach like Helbing’s and combine it with technologies that deal with driver behavior, Orosz says. Car sensors that detect the distance between your bumper and the car in front of you can prevent a sweep of brake-slamming that can tie up traffic, for example.

“In general these algorithms improve traffic, but maybe not as much as they do on paper because we are still human,” he says. “It is still humans driving the cars.”